code: def rule_1(dep_rel, gov_entry, dep_entry, text):
      """Extract term if rule 1 applies.
  
      Args:
          dep_rel (DepRelation): Dependency relation.
          gov_entry (DicEntrySentiment): Governor opinion entry.
          dep_entry (DicEntrySentiment): Dependant opinion entry.
          text (str): Sentence text.
      """
      candidate = None
      (anchor_entry, anchor, related) = (
          (gov_entry, dep_rel.gov, dep_rel.dep)
          if gov_entry
          else (dep_entry, dep_rel.dep, dep_rel.gov)
      )
  
      if related.norm_pos == POS.ADJ and dep_rel.rel.startswith("conj"):
          polarity = anchor_entry.polarity
          candidate = CandidateTerm(related, anchor, text, polarity)
      return candidate
  
file_path: nlp-architect/nlp_architect/models/absa/train/rules.py
imports: from nlp_architect.models.absa.inference.data_types import Polarity
  from nlp_architect.models.absa.train.data_types import CandidateTerm, RelCategory, DepRelationTerm, POS
label_desc: Use image node_id 1 for calling a global function with example usage: rule_1(dep_rel, gov_entry, dep_entry, text) and returns: candidate